Risk Models That Use Postoperative Patient Monitoring Data to Predict Outcomes in Adult Cardiac Surgery: A Systematic Review

Abstract

Risk models that utilise postoperative patient monitoring data to predict outcomes in adult cardiac surgery; a systematic review.

Outcome Prediction After Open Heart Surgery

“…But, this still can be solved if APACHE II score have the ability to predict the risk on daily basis. 19 The SOFA score had good ability to predict mortality (AUC: 0.878, P-value <0.001) in our study. Our results are supported by the results of Ceriani 13 .…”

“…The collected data were organized, tabulated and statistically analyzed using SPSS version 19 Lemeshow test was used to express fitness of the model. The ROC curve was used to test predictability of survival by SOFA, CACUS and APACHE II.…”

Predicting Readmission to Intensive Care After Cardiac Surgery Within Index Hospitalization: A Systematic Review

“…30 Postoperative physiological variables have also been shown to be useful for predicting other complications after cardiac surgery. 36 Xue et. al demonstrated that inclusion of temporal trends in post-operative physiological measurements improved model performance compatred with models solely based on snapshots of physiological values.…”

Validation of Three Postoperative Risk Prediction Models for Intensive Care Unit Mortality after Cardiac Surgery

“…A number of potentially useful models which analyse postoperative data have been developed. Some models designed for use in general intensive care unit (ICU) patients also accurately predict mortality after cardiac surgery, [4][5][6][7][8][9][10][11][12][13][14] with the Sequential Organ Failure Assessment (SOFA) score generally demonstrating the best performance. [7,15] The Cardiac Surgery Risk Score (CASUS) and its derivatives are examples of models designed specifically for use following cardiac surgery.…”